Advancements in triple-negative breast cancer sub-typing, diagnosis and treatment with assistance of artificial intelligence : a focused review.

Triple negative breast cancer (TNBC) is most aggressive type of breast cancer with multiple invasive sub-types and leading cause of women's death worldwide. Lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) causes it to spread rapidly making its treatment challenging due to unresponsiveness towards anti-HER and endocrine therapy. Hence, needing advanced therapeutic treatments and strategies in order to get better recovery from TNBC. Artificial intelligence (AI) has been emerged by giving its high inputs in the automated diagnosis as well as treatment of several diseases, particularly TNBC. AI based TNBC molecular sub-typing, diagnosis as well as therapeutic treatment has become successful now days. Therefore, present review has reviewed recent advancements in the role and assistance of AI particularly focusing on molecular sub-typing, diagnosis as well as treatment of TNBC. Meanwhile, advantages, certain limitations and future implications of AI assistance in the TNBC diagnosis and treatment are also discussed in order to fully understand readers regarding this issue.

Integrating machine learning algorithms and multiple immunohistochemistry validation to unveil novel diagnostic markers based on costimulatory molecules for predicting immune microenvironment status in triple-negative breast cancer.

Introduction: Costimulatory molecules are putative novel targets or potential additions to current available immunotherapy, but their expression patterns and clinical value in triple-negative breast cancer (TNBC) are to be clarified. Methods: The gene expression profiles datasets of TNBC patients were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Diagnostic biomarkers for stratifying individualized tumor immune microenvironment (TIME) were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Additionally, we explored their associations with response to immunotherapy via the multiplex immunohistochemistry (mIHC). Results: A total of 60 costimulatory molecule genes (CMGs) were obtained, and we determined two different TIME subclasses ("hot" and "cold") through the K-means clustering method. The "hot" tumors presented a higher infiltration of activated immune cells, i.e., CD4 memory-activated T cells, resting NK cells, M1 macrophages, and CD8 T cells, thereby enriched in the B cell and T cell receptor signaling pathways. LASSO and SVM-RFE algorithms identified three CMGs (CD86, TNFRSF17 and TNFRSF1B) as diagnostic biomarkers. Following, a novel diagnostic nomogram was constructed for predicting individualized TIME status and was validated with good predictive accuracy in TCGA, GSE76250 and GSE58812 databases. Further mIHC conformed that TNBC patients with high CD86, TNFRSF17 and TNFRSF1B levels tended to respond to immunotherapy. Conclusion: This study supplemented evidence about the value of CMGs in TNBC. In addition, CD86, TNFRSF17 and TNFRSF1B were found as potential biomarkers, significantly promoting TNBC patient selection for immunotherapeutic guidance.

MYB expression by immunohistochemistry is highly specific and sensitive for detection of solid variant of adenoid cystic carcinoma of the breast among all triple-negative breast cancers.

BACKGROUND: Adenoid cystic carcinoma is a rare subtype of triple-negative breast carcinoma. These low-grade tumours, which are treated by simple mastectomy and have an excellent prognosis compared to other triple-negative breast carcinomas. Solid-variant adenoid cystic carcinomas have basaloid features and are difficult to distinguish morphologically from other triple-negative breast cancers. Breast adenoid cystic carcinoma exhibits MYB protein overexpression, which can be detected by immunohistochemistry (IHC). AIM: We compared the IHC expression of MYB in solid-variant adenoid cystic carcinoma with that in other triple-negative breast cancers. METHODS: We conducted IHC staining of 210 samples of triple-negative breast cancers, including solid-variant adenoid cystic carcinoma (n = 17), metaplastic breast carcinoma (n = 44), basaloid triple-negative breast cancer (n = 21), and other triple-negative invasive ductal carcinoma (n = 128). We classified nuclear staining of MYB as diffuse/strong (3+), focal moderate (2+), focal weak (1+), or none (0). RESULTS: All 17 solid/basaloid adenoid cystic carcinoma cases exhibited 3+ MYB expression. Of the 21 solid/basaloid triple-negative breast cancers, one (5%) had 2+ expression, seven (33%) 1+ expression, and 13 (62%) 0 expression. Of the 44 metaplastic carcinoma cases, 39 cases (89%) had no (0) staining, and the other five cases had focal weak (1+) or moderate (2+) staining. Among the 128 triple-negative invasive ductal carcinoma cases, 92 cases (72%) had no (0) staining, 36 cases (28%) exhibited focal weak (1+) or moderate (2+) staining. CONCLUSIONS: Our study revealed diffuse/strong MYB staining (3+) only in solid/basaloid adenoid cystic carcinomas. Thus, we recommend routine MYB IHC staining in triple-negative breast carcinoma with solid/basaloid morphology to improve diagnostic accuracy.

Next-generation biomarkers for prognostic and potential therapeutic enhancement in Triple negative breast cancer.

Triple-negative breast carcinoma (TNBC) is one of the most challenging subtypes of breast carcinoma and it has very limited therapeutic options as it is highly aggressive. The prognostic biomarkers are crucial for early diagnosis of the tumor, it also helps in anticipating the trajectory of the illness and optimizing the therapy options. Several therapeutic biomarkers are being used. Among them, the next-generation biomarkers that include Circulating tumor (ct) DNA, glycogen, lipid, and exosome biomarkers provide intriguing opportunities for enhancing the prognosis of TNBC. Lipid and glycogen biomarkers serve as essential details on the development of the tumor along with the efficacy of the treatment, as it exhibits metabolic alteration linked to TNBC. Several types of biomarkers have predictive abilities in TNBC. Elevated levels are associated with worse outcomes. ctDNA being a noninvasive biomarker reveals the genetic composition of the tumor, as well as helps to monitor the progression of the disease. Traditional therapies are ineffective in TNBC due to a lack of receptors, targeted drug delivery provides a tailored approach to overcome drug resistance and site-specific action by minimizing the side effects in TNBC treatment. This enhances therapeutic outcomes against the aggressive nature of breast cancer. This paper includes all the recent biomarkers which has been researched so far in TNBC and the state of art for TNBC which is explored.

Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing.

Circulating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically comprises thousands of gene expression reads per cell, which artificial intelligence algorithms can accurately analyze. This work presents machine-learning-based classifiers that differentiate CTCs from peripheral blood mononuclear cells (PBMCs) based on single cell RNA sequencing data. We developed four tree-based models and we trained and tested them on a dataset consisting of Smart-Seq2 sequenced data from primary tumor sections of breast cancer patients and PBMCs and on a public dataset with manually annotated CTC expression profiles from 34 metastatic breast patients, including triple-negative breast cancer. Our best models achieved about 95% balanced accuracy on the CTC test set on per cell basis, correctly detecting 133 out of 138 CTCs and CTC-PBMC clusters. Considering the non-invasive character of the liquid biopsy examination and our accurate results, we can conclude that our work has potential application value.

MIF as a potential diagnostic and prognostic biomarker for triple-negative breast cancer that correlates with the polarization of M2 macrophages.

Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine that plays a crucial role in antitumor immunity. However, the role of MIF in influencing the tumor microenvironment (TME) and prognosis of triple-negative breast cancer (TNBC) remains to be elucidated. Using R, we analyzed single-cell RNA sequencing (scRNA-seq) data of 41 567 cells from 10 TNBC tumor samples and spatial transcriptomic data from two patients. Relationships between MIF expression and immune cell infiltration, clinicopathological stage, and survival prognosis were determined using samples from The Cancer Genome Atlas (TCGA) and validated in a clinical cohort using immunohistochemistry. Analysis of scRNA-seq data revealed that MIF secreted by epithelial cells in TNBC patients could regulate the polarization of macrophages into the M2 phenotype, which plays a key role in modulating the TME. Spatial transcriptomic data also showed that epithelial cells (tumor cells) and MIF were proximally located. Analysis of TCGA samples confirmed that tumor tissues of patients with high MIF expression were enriched with M2 macrophages and showed a higher T stage. High MIF expression was significantly associated with poor patient prognosis. Immunohistochemical staining showed high MIF expression was associated with younger patients and worse clinicopathological staging. MIF secreted by epithelial cells may represent a potential biomarker for the diagnosis and prognosis of TNBC and may promote TNBC invasion by remodeling the tumor immune microenvironment.

Emergence of Quantum Dots as Innovative Tools for Early Diagnosis and Advanced Treatment of Breast Cancer.

Quantum dots (QDs) semiconducting nanomaterials, have garnered attention due to their distinctive properties, including small size, high luminescence, and biocompatibility. In the context of triple-negative breast cancer (TNBC), notorious for its resistance to conventional treatments, QDs exhibit promising potential for enhancing diagnostic imaging and providing targeted therapies. This review underscores recent advancements in the utilization of QDs in imaging techniques, such as fluorescence tomography and magnetic resonance imaging, aiming at the early and precise detection of tumors. Emphasis is placed on the significance of QD design, synthesis and functionalization processes as well as their use in innovative strategies for targeted drug delivery, capitalizing on their ability to selectively deliver therapeutic agents to cancer cells. As the research in this field advances rapidly, this review covers a classification of QDs according to their composition, the characterization techniques than can be used to determine their properties and, subsequently, emphasizes recent findings in the field of TNBC-targeting, highlighting the imperative need to address challenges, like potential toxicity or methodologies standardization. Collectively, the findings explored thus far suggest that QDs could pave the way for early diagnosis and effective therapy of TNBC, representing a significant stride toward precise and personalized strategies in treating TNBC.

Artificial intelligence enhances whole-slide interpretation of PD-L1 CPS in triple-negative breast cancer: A multi-institutional ring study.

BACKGROUND AND AIMS: Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability in the consistency and accuracy of the interpretation. It is of great importance to establish an objective and effective method which is highly repeatable. METHODS: We proposed a model in a deep learning-based framework, which at the patch level incorporated cell analysis and tissue region analysis, followed by the whole-slide level fusion of patch results. Three rounds of ring studies (RSs) were conducted. Twenty-one pathologists of different levels from four institutions evaluated the PD-L1 CPS in TNBC specimens as continuous scores by visual assessment and our artificial intelligence (AI)-assisted method. RESULTS: In the visual assessment, the interpretation results of PD-L1 (Dako 22C3) CPS by different levels of pathologists have significant differences and showed weak consistency. Using AI-assisted interpretation, there were no significant differences between all pathologists (P = 0.43), and the intraclass correlation coefficient (ICC) value was increased from 0.618 [95% confidence interval (CI) = 0.524-0.719] to 0.931 (95% CI = 0.902-0.955). The accuracy of interpretation result is further improved to 0.919 (95% CI = 0.886-0.947). Acceptance of AI results by junior pathologists was the highest among all levels, and 80% of the AI results were accepted overall. CONCLUSION: With the help of the AI-assisted diagnostic method, different levels of pathologists achieved excellent consistency and repeatability in the interpretation of PD-L1 (Dako 22C3) CPS. Our AI-assisted diagnostic approach was proved to strengthen the consistency and repeatability in clinical practice.

Metastatic triple-negative breast carcinoma mimicking melanoma: A potential diagnostic pitfall.

Melanoma, with its diverse histopathologic characteristics, can mimic both benign nevi and neoplasms of various cell lineages. Immunohistochemistry (IHC) can play a vital role in melanoma diagnosis, particularly when the cell lineage is unclear on hematoxylin and eosin sections. Commonly utilized IHC stains for melanoma diagnosis include SOX10, Melan-A, and S100. A relatively novel stain, PReferentially expressed Antigen in MElanoma (PRAME), is also proving useful in accurate melanoma diagnosis. However, none of these stains are completely specific to melanocytes or melanoma, and misinterpretation can lead to incorrect diagnoses. This report presents a unique case of triple-negative breast carcinoma (TNBC) metastatic to the skin exhibiting histopathologic characteristics similar to melanoma, including positivity for SOX10 and PRAME. Our aim is to highlight TNBC metastatic to the skin as a potential diagnostic pitfall.

The prognostic marker KRT81 is involved in suppressing CD8 + T cells and predicts immunotherapy response for triple-negative breast cancer.

Triple-negative breast Cancer (TNBC) is an aggressive subtype lacking estrogen, progesterone, and HER2 receptors. Known for limited targeted therapies, it poses challenges and requires personalized treatment strategies. Differential analysis revealed a significant decrease in keratin 81 (KRT81) expression in non-TNBC samples and an increase in TNBC samples, lower KRT81 expression correlated with better TNBC patient outcomes. It emerged as an independent predictive factor for TNBC, with associations found between its expression and clinically relevant features. We further developed a nomogram for survival probability assessment based on Cox regression results, demonstrating its accuracy through calibration curves. Gene annotation analysis indicated that KRT81 is involved in immune-related pathways and tumor cell adhesion. KRT81 is associated with immune cell infiltration of Follicular helper T cells (Tfh) and CD8 + T cells, suggesting its potential impact on the immunological microenvironment. The study delved into KRT81's predictive value for immunotherapy responses, high expression of KRT81 was associated with greater potential for immune evasion. Single-cell RNA sequencing analysis pinpointed KRT81 expression within a specific malignant subtype which was a risk factor for TNBC. Furthermore, KRT81 promoted TNBC cell proliferation, migration, invasion, and adhesion was confirmed by gene knockout or overexpression assay. Co-culture experiments further indicated KRT81's potential role in inhibiting CD8 + T cells, and correlation analysis implied KRT81 was highly correlated with immune checkpoint CD276, providing insights into its involvement in the immune microenvironment via CD276. In conclusion, this comprehensive study positions KRT81 as a promising prognostic marker for predicting tumor progression and immunotherapy responses in TNBC.

Subtyping of triple-negative breast cancers: its prognostication and implications in diagnosis of breast origin.

BACKGROUND: Triple-negative breast cancer (TNBC) subtyping by gene profiling has provided valuable clinical information. Here, we aimed to evaluate the relevance of TNBC subtyping using immunohistochemistry (IHC), which could be a more clinically practical approach, for prognostication and applications in patient management. METHODS: A total of 123 TNBC cases were classified using androgen receptor (AR), CD8, Forkhead box C1 protein (FOXC1), and doublecortin-like kinase 1 (DCLK1) into luminal androgen receptor (LAR), basal-like immunosuppressive (BLIS), mesenchymal-like (MES), and immunomodulatory (IM) subtypes. The IM cases were further divided into the IM-excluded and IM-inflamed categories by CD8 spatial distribution. Their clinicopathological and biomarker profiles and prognoses were evaluated. RESULTS: LAR (28.6%) and MES (11.2%) were the most and least frequent subtypes. The IHC-TNBC subtypes demonstrated distinct clinicopathological features and biomarker profiles, corresponding to the reported features in gene profiling studies. IM-inflamed subtype had the best outcome, while BLIS had a significantly poorer survival. Differential breast-specific marker expressions were found. Trichorhinophalangeal syndrome type 1 (TRPS1) was more sensitive for IM-inflamed and BLIS, GATA-binding protein 3 (GATA3) for IM-excluded and MES, and gross cystic disease fluid protein 15 (GCDFP15) for LAR subtypes. CONCLUSIONS: Our findings demonstrated the feasibility of IHC surrogates to stratify TNBC subtypes with distinct features and prognoses. The IM subtype can be refined by its CD8 spatial pattern. Breast-specific marker expression varied among the subtypes. Marker selection should be tailored accordingly.

Utility of human epidermal growth factor 2 heterogeneity as a prognostic factor in triple-negative breast cancer.

In some cases of human epidermal growth factor 2 (HER2)-negative breast cancer, including triple-negative breast cancer, HER2 expression is sporadically and strongly upregulated, a condition known as HER2 heterogeneity. We investigated the clinicopathological features of patients with HER2 heterogeneity in triple-negative breast cancers treated with neoadjuvant chemotherapy. Thirty-nine patients with triple-negative breast cancer who had undergone preoperative chemotherapy participated in this study. To assess for HER2 heterogeneity, we used dual in situ hybridization slides. We evaluated the association between HER2 heterogeneity and clinicopathological factors such as rates of pathologic complete response (pCR) and of recurrence-free survival. Of the 39 patients, 15 (38.5%) had cancers with HER2 heterogeneity. The pCR rates were 13.3% among patients with HER2 heterogeneity and 20.8% among those with HER2 nonheterogeneity, but the difference was not significant. The recurrence-free survival rate was significantly lower in patients with HER2 heterogeneity than in those without (P = 0.025). HER2 heterogeneity is a significant predictor of poor prognosis in patients with triple-negative breast cancer treated with neoadjuvant chemotherapy.

Diagnostic utility and sensitivities of matrix Gla protein (MGP), TRPS1 and GATA3 in breast cancer: focusing on metastatic breast cancer, invasive breast carcinoma with special features, and salivary gland-type tumours.

Matrix Gla protein (MGP) and trichorhinophalangeal syndrome type 1 (TRPS1) have recently emerged as novel breast-specific immunohistochemical (IHC) markers, particularly for triple-negative breast cancer (TNBC) and metaplastic carcinoma. The present study aimed to validate and compare the expression of MGP, TRPS1 and GATA binding protein 3 (GATA3) in metastatic breast carcinoma (MBC), invasive breast carcinoma (IBC) with special features, including special types of invasive breast carcinoma (IBC-STs) and invasive breast carcinoma of no special type with unique features, and mammary and non-mammary salivary gland-type tumours (SGTs). Among all enrolled cases, MGP, TRPS1 and GATA3 had comparable high positivity for ER/PR-positive (p=0.148) and HER2-positive (p=0.310) breast carcinoma (BC), while GATA3 positivity was significantly lower in TNBC (p<0.001). Similarly, the positive rates of MGP and TRPS1 in MBCs (99.4%), were higher than in GATA3 (90.9%, p<0.001). Among the IBC-STs, 98.4% of invasive lobular carcinomas (ILCs) were positive for all three markers. Among neuroendocrine tumours (NTs), all cases were positive for TRPS1 and GATA3, while MGP positivity was relatively low (81.8%, p=0.313). In the neuroendocrine carcinoma (NC) subgroup, all cases were positive for GATA3 and MGP, while one case was negative for TRPS1. All carcinomas with apocrine differentiation (APOs) were positive for GATA3 and MGP, while only 60% of the cases demonstrated moderate staining for TRPS1. Among mammary SGTs, MGP demonstrated the highest positivity (100%), followed by TRPS1 (96.0%) and GATA3 (72.0%). Positive staining for these markers was also frequently observed in non-mammary SGTs. Our findings further validate the high sensitivity of MGP and TRPS1 in MBCs, IBC-STs, and breast SGTs. However, none of these markers are capable of distinguishing between mammary and non-mammary SGTs.

Quantification of MicroRNA in a Single Living Cell via Ionic Current Rectification-Based Nanopore for Triple Negative Breast Cancer Diagnosis.

Accurate analysis of microRNAs (miRNAs) at the single-cell level is extremely important for deeply understanding their multiple and intricate biological functions. Despite some advancements in analyzing single-cell miRNAs, challenges such as intracellular interferences and insufficient detection limits still remain. In this work, an ultrasensitive nanopore sensor for quantitative single-cell miRNA-155 detection is constructed based on ionic current rectification (ICR) coupled with enzyme-free catalytic hairpin assembly (CHA). Benefiting from the enzyme-free CHA amplification strategy, the detection limit of the nanopore sensor for miRNA-155 reaches 10 fM and the nanopore sensor is more adaptable to complex intracellular environments. With the nanopore sensor, the concentration of miRNA-155 in living single cells is quantified to realize the early diagnosis of triple-negative breast cancer (TNBC). Furthermore, the nanopore sensor can be applied in screening anticancer drugs by tracking the expression level of miRNA-155. This work provides an adaptive and universal method for quantitatively analyzing intracellular miRNAs, which will greatly improve our understanding of cell heterogeneity and provide a more reliable scientific basis for exploring major diseases at the single-cell level.

A 14-gene B-cell immune signature in early-stage triple-negative breast cancer (TNBC): a pooled analysis of seven studies.

BACKGROUND: Early-stage triple-negative breast cancer (TNBC) displays clinical and biological diversity. From a biological standpoint, immune infiltration plays a crucial role in TNBC prognosis. Currently, there is a lack of genomic tools aiding in treatment decisions for TNBC. This study aims to assess the effectiveness of a B-cell/immunoglobulin signature (IGG) alone, or in combination with tumor burden, in predicting prognosis and treatment response in patients with TNBC. METHODS: Genomic and clinical data were retrieved from 7 cohorts: SCAN-B (N = 874), BrighTNess (n = 482), CALGB-40603 (n = 389), METABRIC (n = 267), TCGA (n = 118), GSE58812 (n = 107), GSE21653 (n = 67). IGG and a risk score integrating IGG with tumor/nodal staging (IGG-Clin) were assessed for event-free survival (EFS) and overall survival (OS) in each cohort. Random effects model was used to derive pooled effect sizes. Association of IGG with pathological complete response (pCR) was assessed in CALGB-40603 and BrighTNess. Immune significance of IGG was estimated through CIBERSORTx and EcoTyper. FINDINGS: IGG was associated with improved EFS (pooled HR = 0.77, [95% CI = 0.70-0.85], I2 = 18%) and OS (pooled HR = 0.79, [0.73-0.85], I2 = 0%) across cohorts, and was predictive of pCR in CALGB-40603 (OR 1.25, [1.10-1.50]) and BrighTNess (OR 1.57 [1.25-1.98]). IGG-Clin was predictive of recurrence (pooled HR = 2.11, [1.75-2.55], I2 = 0%) and death (pooled HR = 1.99, 95% [0.84-4.73], I2 = 79%) across cohorts. IGG was associated with adaptive immune response at CIBERSORTx and EcoTyper analysis. INTERPRETATION: IGG is linked to improved prognosis and pCR in early-stage TNBC. The integration of IGG alongside tumor and nodal staging holds promise as an approach to identify patients benefitting from intensified or de-intensified treatments. FUNDING: This study received funding from: Associació Beca Marta Santamaria, European Union's Horizon 2020 research and innovation and Marie Sklodowska-Curie Actions programs, Fundación FERO, Fundación CRIS contra el cáncer, Agència de Gestó d'Ajuts Universitaris i de Recerca, Instituto de Salud Carlos III, Fundación Contigo, Asociación Cáncer de Mama Metastásico IV, Breast Cancer Research Foundation, RESCUER, Fundación científica AECC and FSEOM.

Aging-accumulated methylmalonic acid serum levels at breast cancer diagnosis are not associated with distant metastases.

PURPOSE: Recent evidence suggests that age-accumulated methylmalonic acid (MMA) promotes breast cancer progression in mice. This study aims to investigate the association between baseline serum MMA concentrations in patients with breast cancer and the development of subsequent distant metastases. METHODS: We included 32 patients with early Luminal B-like breast cancer (LumB, median age 62.4y) and 52 patients with early triple-negative breast cancer (TNBC, median age 50.5y) who developed distant metastases within 5 years. They were matched to an equal number of early breast cancer patients (median age 62.2y for LumB and 50.5y for TNBC) who did not develop distant metastases with at least 5 years of follow-up. RESULTS: Baseline serum MMA levels at breast cancer diagnosis showed a positive correlation with age (P < 0.001) and a negative correlation with renal function and vitamin B12 (all P < 0.02), but no statistical association was found with BMI or tumor stage (P > 0.6). Between matched pairs, no significant difference was observed in MMA levels, after adjusting for kidney function and age (P = 0.19). Additionally, in a mouse model, a significant decline in MMA levels was observed in the tumor-bearing group compared to the group without tumors before and after tumor establishment or at identical times for the control group (P = 0.03). CONCLUSION: Baseline serum MMA levels in patients with breast cancer are not correlated with secondary distant metastasis. Evidence in the mouse model suggests that the presence of a tumor perturbates MMA levels.

[Guidelines for clinical diagnosis and treatment of advanced triple negative breast cancer in China（2024 edition）].

Breast cancer ranks as the most common female malignancy worldwide. Data from GLOBOCAN 2020 showed that breast cancer surpassed lung cancer and become the leading malignancy globally which was a serious threat to women's health. Different from Caucasian, there is a lower prevalence of breast cancer in Chinese women. But the age-standardized incidence rate of breast cancer in China has reached to 39.1 per 100,000 in 2020, with 416,000 new cases, accounting for 18.4% of global breast cancer burden, due to multiple factors such as lifestyle and dietary habits changes in recent years[1]. The treatment and prevention of breast cancer are becoming increasingly a tuff task. In addition, triple-negative breast cancer (TNBC) is a subtype with higher malignancy and worse prognosis. Due to lack of specific therapeutic targets, less treatment progress has been made in recent years. There is even less progress in the therapy of advanced TNBC, but huge unmet needs exist for further therapeutic optimization. Echoing advocacy from The Society of Breast Cancer China Anti-Cancer Association; International Medical Exchange Society, Chinese Anti-Cancer Association; Breast Cancer Group, Branch of Oncologist, Chinese Medical Doctor Association, top experts from multidisciplinary departments of breast cancer in China have consensus on this "Guidelines for Clinical Diagnosis and Treatment of Advanced Triple-Negative Breast Cancer in China (2024 Edition)" according to the latest evidence based updates. We hope this pater can guide or optimize the precise therapeutic decision-making for advanced triple-negative breast cancer in China.

Treatment patterns, healthcare resource utilization and outcomes for early stage triple-negative breast cancer in Japan.

Aim: There is limited information regarding the treatment and outcomes of early stage triple-negative breast cancer (esTNBC) in real-world settings in Japan. Materials & methods: Retrospective analyses of the Medical Data Vision database assessed treatment patterns, healthcare resource utilization (HCRU), patient characteristics, outcomes and prognostic factors among four groups (neoadjuvant therapy+surgery+adjuvant therapy; neoadjuvant therapy+surgery; surgery+adjuvant therapy; surgery only) of esTNBC patients. Results: Treatment patterns, HCRU and demographics varied among the four groups. HCRU was greater and prognosis tended to be worse in the neoadjuvant+surgery+adjuvant therapy group. Conclusion: Our results provide insights into the treatment practices, HCRU and prognosis of esTNBC in Japan. The treatment practices were heterogeneous, reflecting the decision-making process in Japan during the study period.

Triple-negative breast cancer (TNBC) is a cancer type that does not express three biomarkers (estrogen receptors, progesterone receptors and human epidermal growth factor receptor 2), which results in a lack of targeted treatment strategies. Early stage TNBC (esTNBC) is mainly treated by anticancer drugs before (neoadjuvant) and/or after (adjuvant) surgery and adjuvant radiotherapy. New therapies including an immune checkpoint inhibitor which helps better immune system and a PARP inhibitor which helps repair DNA damage were approved for esTNBC in 2022 in Japan, and they are expected to change the treatment options for TNBC. However, there are limited data about the treatment patterns, healthcare resource utilization (HCRU) and outcomes for esTNBC in real-world clinical practice in Japan. Therefore, a hospital-based administrative database was analyzed to understand the treatment patterns for patients with esTNBC in Japan, the HCRU, treatment outcomes (overall survival and event free survival), and the associated factors. Patients received a large variety of treatments before and after surgery. Patients who received both neoadjuvant and adjuvant therapies tended to have more severe disease and required greater HCRU, and their outcomes were worse than patients who received neoadjuvant treatment only, adjuvant treatment only or neither neoadjuvant nor adjuvant treatment. Our findings will help us understand how new treatments will impact the treatment practices and patient outcomes in the future.

[Phosphoproteomics in the diagnosis and treatment of triple-negative breast cancer: a review].

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer. Currently, chemotherapy remains to be the primary treatment for TNBC, but drug resistance is common while patient prognosis is poor. With the development of proteomics technology, phosphoproteomics research has made great progress and has been widely used in the study of tumor mechanism, diagnosis and treatment. Similarly, phosphoproteomics plays a significant role in the studies of the occurrence, development, targeted therapy, and drug resistance mechanisms of TNBC. This article summarizes the research progress of phosphoproteomics in TNBC, with the aim to facilitate the research on the mechanism and treatment of TNBC based on phosphoproteomics.

Triple-Negative or Close-to-Triple-Negative Breast Cancer Presenting as a Thick-Walled Cystic Lesion.

Clinical and pathologic characteristics of the invasive ductal carcinoma (IDC) presenting as a thick-walled breast cyst are little known. Three female patients were included in this report. A palpable, nontender breast lump was found in all cases. While mammography showed a hyperdense mass, ultrasonography demonstrated a thick-walled cystic mass. Magnetic resonance imaging clearly showed the cystic breast lesions with ring-like or irregular rim enhancement. A grade III IDC was confirmed in all cases. All IDCs but one were estrogen receptor negative, progesterone receptor negative, and human epidermal growth factor receptor 2 negative, with merely weak progesterone receptor positivity (5%) in one case. All cases underwent surgical management first and postoperative chemotherapy. Breast malignancy presenting as a thick-walled cystic mass could be a highly aggressive IDC, even triple-negative breast cancer. It is imperative for breast cancer-related practitioners to identify the potentially malignant cystic lesions timely and adopt appropriate management.